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Scenic sat-nav uses neural networks to find the best route

The Autobahn system has already been used to categorise all of Belgium's motorways. In this map green squares represent views of nature or woodlands, blue is water, red is sightseeing, yellow is fields, orange is mountains and black is non-scenic

Nina Runge, Pavel Samsonov, Donald Degraen, Johannes Schöning

Sat-navs have made it easier and quicker then ever to get from A to B, but what if you want to see some of the world? A new artificial intelligence system aims to do just that, using neural a network to analyse Google Street View images and find the most scenic routes.

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The system divides Street View images up into blocks before analysing them to pick out views of mountains, ocean, forests and farmland.

Nina Runge, a computer scientist from the University of Bremen who worked on the Autobahn project, explained that existing systems relied on guessing where good views ought to be, rather than actual data. "Other approaches determine the most scenic points based on the distance to some areas, but these views might be blocked. The Autobahn system uses the actual views," she told WIRED.

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The system uses a neural network to interpret scenic views in Google Street View images

Nina Runge, Pavel Samsonov, Donald Degraen, Johannes Schöning

Runge and colleagues from Belgium's Hasslet University split up Street View panoramas into squares before feeding them into a neural network for categorisation. To plan a route, a user needs to provide a start and end point, maximum journey time and a preference for what they want to see. The AI then plots a route with the best views.

The AI system has already been tested on the Spanish island of Mallorca, Rhone-Alpes in France and Madeira in Portugal, while all of Belgium's motorways have also been categorised. "We determine if a cell shows, for example, mountains, the ocean or a non-scenic view," explained Runge. "Then we compute a route which contains as many scenic points as possible without making long detours."

The system was first tested with 24 participants and compared to journey times over the fastest routes. Most preferred the scenic route, even if it took slightly longer.

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might be some years off, she sees the technology as ideally suited for the vehicles of the future. "In driverless cars this might be a genuine feature for their success, but already today this is very attractive for people who are going on holidays by car or with a camper, convertible or motorbike."

The next step for the Autobahn system will be to test it in more areas and see how well the neural network is able to categorise different types of scenery. Runge hopes the technology will eventually be integrated into existing route-planning apps.